Are there particular pros and cons to the scale of each individual turbine? I think this is the first time I've seen that figure reported as opposed to the capacity of the wind farm as a whole
With larger turbines you need fewer for the same capacity. This means less manufacturing, easier maintenance, they are taller, which means more stable and stronger wind, and a lower price of construction. However larger turbines also lead to greater stresses on the system, so that can again increase maintenance and large blades are hard to transport on land.
So it is a compromise. Up to now offshore wind turbine manufacturers always built bigger turbines with newer generations. However the engineering challenges increases, so many have stopped going for bigger then 14-16MW and instead go for increased numbers of turbines with higher reliability.
Over a large range of sizes for many physical reasons larger turbines can be more efficient per space and per cost. For example there is less ground effects for larger turbines and the rotor area scales quadratically with hub height.
Who knows, commercial fusion power might actually be less than 50 years away now. LOL.
Edit: Do keep in mind that this stuff doesn't have to be the efficiency of the Sun because the Sun is actually quite inefficient and takes millions of years for the heat to get from the core where it is fused out into the galaxy. They have to be hotter than the temperature of the Sun and more efficient.
They have to be hotter than the temperature of the Sun
Well they don't strictly speaking have to but to get fusion you need a combination of pressure and temperature and increasing temperature is way easier than increasing pressure if you don't happen to have the gravity of the sun to help you out. Compressing things with magnetic fields isn't exactly easy.
Efficiency in a fusion reactor would be how much of the fusion energy is captured, then how much of it you need to keep the fusion going, everything from plasma heating to cooling down the coils. Fuel costs are very small in comparison to everything else so being a bit wasteful isn't actually that bad if it doesn't make the reactor otherwise more expensive.
What's much more important is to be economical: All the currently-existing reactors are research reactors, they don't care about operating costs, what the Max Planck people are currently figuring out is exactly that kind of stuff, "do we use a cheap material for the diverters and exchange them regularly, or do we use something fancy and service the reactor less often": That's an economical question, one that makes the reactor cheaper to operate so the overall price per kWh is lower. They're planning on having the first commercial prototype up and running in the early 2030s. If they can achieve per kWh fuel and operating costs lower than gas they've won, even though levelised costs (that is, including construction of the plant amortised over time) will definitely still need lowering. Can't exactly buy superconducting coils off the shelf right now, least of all in those odd shapes that stellerators use.
Fusion is a field where you can't have the "statup mindset": investments are in hundreds of millions and take at best a decade (and most likely two) to pay off. That's one field where it can't go anywhere without public funding.
It is very possible that China gets there first, considering how ridiculous western fusion efforts have been.
We've proved we can do fusion, but we're still at the stage of just having singular reactions. None of these are power stations with a continuous flow of output, and they're not even close to being so.
Currently, the highest Q value obtained from a tokamak is 1.53
I'm pretty sure this is the value of Q achieved by the National Ignition Facility, which uses inertial confinement, not a tokamak. As far as I know, the record Q for a tokamak is still only 0.67, set by the Joint European Torus back in 1997.
I just can't trust innovations and discoveries coming from China, I'm excited, but I'll hold my breath until it's been replicated by a less untrustworthy source
Figure announced during its deployment in January that the robots would undergo training for twelve to twenty-four months. After this training period, they will be integrated into the facility with the precise skills required for each task.
That's a pretty long training period. I wonder if any of the training data is reusable if the assembly process changes slightly?
Figure aims to create a global model that can manage billion-unit humanoid robots. The company points out that there are about 10 million unsafe or undesirable jobs in the US alone.
Not sure how I feel about 10M workers being dismissed over time... the robot itself is really impressive regardless
From what I understand this is the first time training of the system. It's brand new. Its going to take a while.
Some that would be analogous would be those arm robots. At the start they were very specific and I don't think very flexible at all. But when I looked at them going into a factory they are very general purpose machines. The manufacturers would come out and install them and make changes easily. They were also talking about how they would train people onsite to make some alterations, e.g. new box sizes.
Seeing as its using neural networks, they are meant to be general purpose machines right? I'm sure they must be more flexible than other types of systems.
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